Machine Learning Engineer
Description For Machine Learning Engineer
Bree is an innovative consumer finance platform revolutionizing financial services in Canada, specifically targeting the underserved market of individuals living paycheck to paycheck. With over 400,000 Canadian users and growing rapidly, Bree is positioned as a leading FinTech company in Canada, boasting 8-figure annualized revenue and profitable operations.
As a Machine Learning Engineer at Bree, you'll be at the forefront of building and scaling sophisticated ML systems that power critical financial decisions. The role combines technical expertise in ML with practical implementation, requiring proficiency in Python, various ML libraries, and modern MLOps practices. You'll work on end-to-end ML pipelines, from development to deployment, using cutting-edge tools and technologies.
The position offers an exciting opportunity to make a significant impact in a fast-growing startup that's already demonstrated product-market fit. You'll be joining a stable team with zero voluntary employee turnover, backed by Y Combinator and substantial seed funding. The comprehensive benefits package, including learning stipends, wellness benefits, and unlimited PTO, reflects Bree's commitment to employee growth and well-being.
This role is perfect for a skilled ML engineer who wants to apply their expertise in a meaningful way, helping to improve financial services for millions of Canadians while working with modern technologies and practices in a supportive, growth-oriented environment.
Responsibilities For Machine Learning Engineer
- Design, develop, and deploy end-to-end machine learning pipelines
- Implement MLOps best practices, including CI/CD for ML models
- Optimize ML models using feature engineering and hyperparameter tuning
- Work with structured and unstructured data using Pandas, NumPy, and SQL
- Apply machine learning design patterns
- Collaborate with data engineers on high-performance data pipelines
- Deploy and manage models on cloud platforms
- Maintain model performance and implement monitoring
Requirements For Machine Learning Engineer
- Proficiency in Python and ML libraries like Scikit-learn, LightGBM, and PyTorch
- Strong understanding of machine learning algorithms
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker
- Hands-on experience with data manipulation libraries and databases
- Knowledge of cloud-based ML deployment
- Ability to implement real-time and batch inference pipelines
- Strong analytical and problem-solving skills
- Eagerness to work in a fast-paced environment
Benefits For Machine Learning Engineer
- Top of the market compensation for top performers
- Comprehensive dental / vision
- $1,500 annual learning stipend
- $1,000 annual wellness stipend
- $250 monthly lunch stipend
- 2 annual company retreats
- Parental leave
- Unlimited PTO
